CBMS Regional Research Conference on Topological Data Analysis

会议，“拓扑数据分析：理论与应用”，将于2017年6月12日至16日在Macalaster学院（圣保罗，MN）举行。拓扑数据分析（TDA）是数学、统计学和计算机科学交叉的一个相对较新且发展迅速的研究领域。会议的目标是鼓励教师和学生，特别是在主要的本科院校，谁可能没有与TDA的经验，在TDA的研究。因此，本次会议将吸引来自中西部各州的学院和大学的教师，研究生和高级本科生。会议的目的是让与会者不仅TDA的理论框架，而且还实用的计算工具，提供入口点，使教师和学生从不同的设置可以开始研究拓扑数据分析，并将这项工作纳入他们的教学。会议将促进机构之间和跨学科的新的研究合作。由此产生的专着，编写的首席讲师博士Vin de Silva，数学副教授在波莫纳学院，应该感兴趣的数学家，科学家和学生。近年来，拓扑数据分析（TDA）引起了数学家和科学家的广泛兴趣，他们正在寻找新的工具来分析来自神经科学，数字成像，遗传学，生物聚合，传感器网络，癌症研究和其他领域的日益增长的复杂数据。TDA的智力吸引力来自于其结合了高等数学，尖端算法和实际应用。然而，尽管它的数学复杂性，TDA方法是令人惊讶的直观，并借给自己很好的研究与学生，甚至在本科阶段。本次会议的主要演讲者将是Vin de Silva博士，他是TDA发展的关键贡献者。讲座主题将包括缠绕数，单纯同调和上同调，持久性算法，稳定性定理，锯齿持久性，范畴理论和广义持久性，和Reeb cosheaves。除了讲座外，会议还将举办实验室会议，为与会者提供使用最先进的TDA软件分析真实的数据的实践经验，以及突出学生参与的TDA研究的海报会议。这次会议将集中在数学和计算，而不是统计，它将强调在设置主要是本科院校的研究。有关会议的信息可在http://pages.stolaf.edu/tda-conference/

The conference, "Topological Data Analysis: Theory and Applications," will take place at Macalaster College (St. Paul, MN) from June 12-16, 2017. Topological Data Analysis (TDA) is a relatively recent and quickly-developing area of research at the intersection of mathematics, statistics, and computer science. The goal of the conference is to encourage research in TDA by faculty and students, especially at primarily undergraduate institutions, who might not have prior experience with TDA. As such, this conference will attract faculty, graduate students, and advanced undergraduates from colleges and universities across the upper Midwestern states. The conference is designed to equip attendees with not only the theoretical framework of TDA, but also practical computational tools, providing points of entry so that faculty and students from diverse settings can begin research in topological data analysis and incorporate this work into their teaching. The conference will spur new research collaborations between institutions and across disciplines. The resulting monograph, prepared by principal lecturer Dr. Vin de Silva, Associate Professor of Mathematics at Pomona College, should be of interest to mathematicians, scientists and students. In recent years, Topological Data Analysis (TDA) has attracted widespread interest from mathematicians and scientists looking for new tools to analyze ever increasing amounts of complex data arising from neuroscience, digital imaging, genetics, biological aggregations, sensor networks, cancer research, and other areas. The intellectual appeal of TDA arises from its combination of advanced mathematics, cutting-edge algorithms, and practical applications. Yet, despite its mathematical sophistication, TDA methodology is surprisingly intuitive and lends itself well to research with students, even at the undergraduate level. The principal lecturer at this conference will be Dr. Vin de Silva who has been a key contributor to the development of TDA. Lecture topics will include winding numbers, simplicial homology and cohomology, the persistence algorithm, stability theorems, zigzag persistence, category theory and generalized persistence, and Reeb cosheaves. In addition to lectures, the conference will feature lab sessions that will offer participants hands-on experience analyzing real data using state-of-the-art TDA software, as well as a poster session highlighting TDA research involving students. This conference will focus on mathematics and computation rather than statistics, and it will emphasize research in the setting of primarily undergraduate institutions.Information about the conference is available at http://pages.stolaf.edu/tda-conference/